Random and Quasi-Random Point Sets

Hellekalek, Peter, and Gerhard Larcher, editors

ISBN 10: 0387985549 / ISBN 13: 9780387985541

Published by Springer, New York, 1998

About this Item

An ex-library copy in original tan paper covers. The usual ex-libris markings. The binding is sound, the text is clean/unmarked, and there is little cover wear.

Seller Inventory # 063948

Bibliographic Details

• Title: Random and Quasi-Random Point Sets
• Publisher: Springer, New York
• Publication Date: 1998
• Language: English
• ISBN 10: 0387985549
• ISBN 13: 9780387985541
• Binding: Trade Paperback
• Edition: First Edition.
• Condition: Good
• Dust Jacket Condition: No Dust Jacket
• Book Type: Book

About this title

Synopsis

This volume is a collection of survey papers on recent developments in the fields of quasi-Monte Carlo methods and uniform random number generation. We will cover a broad spectrum of questions, from advanced metric number theory to pricing financial derivatives. The Monte Carlo method is one of the most important tools of system modeling. Deterministic algorithms, so-called uniform random number gen­ erators, are used to produce the input for the model systems on computers. Such generators are assessed by theoretical ("a priori") and by empirical tests. In the a priori analysis, we study figures of merit that measure the uniformity of certain high-dimensional "random" point sets. The degree of uniformity is strongly related to the degree of correlations within the random numbers. The quasi-Monte Carlo approach aims at improving the rate of conver­ gence in the Monte Carlo method by number-theoretic techniques. It yields deterministic bounds for the approximation error. The main mathematical tool here are so-called low-discrepancy sequences. These "quasi-random" points are produced by deterministic algorithms and should be as "super"­ uniformly distributed as possible. Hence, both in uniform random number generation and in quasi-Monte Carlo methods, we study the uniformity of deterministically generated point sets in high dimensions. By a (common) abuse oflanguage, one speaks of random and quasi-random point sets. The central questions treated in this book are (i) how to generate, (ii) how to analyze, and (iii) how to apply such high-dimensional point sets.